The present invention relates generally to digital image processing, and more specifically to a method and apparatus for electronically converting images from one resolution to another with improved image qualify by spatially offsetting the registration between the two resolutions.
Image information, be it color or black and white, is commonly generated by an image input terminal (IIT) in a raster format at a particular resolution and depth K x L x b, where K is a number of spots per unit of length in one dimension, L is a number of spots per unit length in the other dimension, and b is the depth or number of gray or color levels of each pixel (picture element). Image input terminals (IITs) that generate raster image information include scanners and computer image drivers. Image information from an IIT is typically in a format that is adapted to match the capabilities of a particular image output terminal (IOT) to which image information is to be reproduced (printed or displayed). Consequently, resolution conversion, i.e., converting a raster from first resolution and depth K x L x b to second resolution and depth M x N x d, is an important interoperability enabler in distributed imaging environments that have IITs and IOTs with different device resolution and density.
Distributed imaging environments require that a digital image is created at one resolution and printed, archived or displayed at another resolution. Ideally, resolution conversion of raster images should appear fast and transparent to users, while causing little if any image degradation. Increasingly, the resolution available from printers varies over a wider range. Printer resolutions are available over a range, for example, from less than 200 spi to to more than 600 spi. Printer resolutions vary for a number of reasons that generally are related to image quality. Simply printing a 300 spi bitmap at 400 spi or 600 spi is undesirable, however, since the image will be reduced substantially in size on the output page or display. It is therefor highly desirable to provide the capability of printing any image at any resolution, while selecting the output size. Scaling, or magnification and reduction is an operation essentially identical to resolution conversion, except that in scaling the objective is to obtain an image that is a different size at the same resolution. For these reasons, current image processing technology is focused upon means for converting image data from a first resolution to a second resolution.
Simple methods of resolution conversion are fast in terms of speed but generally have a tendency to generate very poor image quality. Bit doubling of an original bitmap image, for example, is a simple scheme leaving a large number of problems unresolved. Among these problems are image erosion and dilation, which occur when images are optimized for write-white or write-black printers. Erosion occurs when images destined for write-black printers are sent to write-white printers resulting in thinner lines than desired. Examples of methods that alleviate erosion problems are disclosed by Eschbach in "Converting between Write-White, Write-Black, and Neutral Bitmaps", Xerox Disclosure Journal, Vol. 17, No. 3 May/June 1992, p. 181, and U.S. patent application Ser. No. 07/588,125 by Mailloux, now U.S. Pat. No. 5,410,615, entitled "Bitmap Image Resolution Converter Compensating for Write-White Xerographic Laser Printing", Filed Sep. 25, 1990 published in JP-A 4-299663 on Oct. 22, 1992. Another problem with simpler forms of resolution conversion is halfbitting. Halfbitting optimizations occur in lower resolution images in order to achieve a higher resolution effect at image edges. Both halfbitting and erosion and dilation problems occur because bit doubling does not preserve the local density intent of an image over a given area. As a result, artifacts are produced giving a resolution converted image a different appearance from an original.
Methods that convert gray images to binary or another number of levels while attempting to preserve the local density of an image over a given area exist in applications separate from resolution conversion. These and similar methods might be applied as one part of the method in resolution conversion. One method, which can be used to prepare an image at a given resolution and density of I x J x a for printing on a printer with resolution M x N x d, is error diffusion as described in "An Adaptive Algorithm for Spatial Greyscale, by Floyd and Steinberg, Proc. of the S.I.D. 17/2, 75-77 (1976) (hereinafter, "Floyd and Steinberg"). Current distributed environments require a greater degree of flexibility from resolution conversion schemes, as the following more recent advances teach.
More elaborate methods of resolution conversion other than pixel doubling have been developed that are slower than simple methods but are still quite fast and result in better but not perfect image quality. For example, linear combination resolution conversion techniques such as area mapping as taught by Coward in "Area Mapping Table Look Up Scheme", Xerox Disclosure Journal, Vol. 18, No. 2, March/April 1993, p. 217, and by Papaconstantinou in "Hardware Architecture For Resolution Conversion Using Area Mapping", Xerox Disclosure Journal, Vol. 18, No. 5, September/October 1993, p. 553, and nearest neighbor taught by Coward et al. in "Hardware Architecture for Nearest Neighbor Image Processing Algorithms", Xerox Disclosure Journal, Vol. 18, No. 4, July/August 1993, p. 451, provide inadequate image quality when converting halftone images. More specifically, linear combination resolution conversion techniques have a tendency to create errors at boundaries of tiled images that are spatially oriented using a template. Other elaborate methods of resolution conversion of interest include: U.S. patent application Ser. No. 07/513,415, entitled " Bit-Map Image Resolution Converter", now U.S. Pat. No. 5,282,057, filed Apr. 12, 1990 (published at JP-A 4-227584 on Aug. 12, 1992) contemplates a method of magnifying, by a predetermined magnification factor (n), the original image pixels in two dimensions. U.S. patent application Ser. No. 07/737,297, entitled "Method of Resolution Conversion", now U.S. Pat. No. 5,282,051, filed Jul. 29, 1991 (published at EP-A2 0 525 996 on Feb. 3, 1993) discloses a method that determines correlation values for a plurality of input pixels to obtain the intensity of the output pixels. Also of interest are the following applications: U.S. patent application Ser. No. 07/981,678, filed Nov. 25, 1992, to Kang et al., now U.S. Pat. No. 5,301,037, entitled Resolution Conversion With Simulated Multi-Bit Gray; U.S. patent application Ser. No. 7/802,790, filed Dec. 6, 1991, to Eschbach, now U.S. Pat. No. 5,293,254, entitled "Method for Maintaining Bit Density While Converting Images In Scale or Resolution"; and U.S. patent application Ser. No. 07/981,720, filed Nov. 25, 1992, to Kang, now U.S. Pat. No. 5,270,836, entitled "Resolution Conversion of Bitmap Images".
Employing sophisticated resolution conversion techniques does not insure that the resulting output image will have a desirable appearance. For instance, the output image can be excessively blocky and/or contain noticeable "jaggies." Hence, smoothing operations are sometimes used in conjunction with the conversion or scaling of the image as disclosed in U.S. patent application Ser. No. 07/895,063 entitled "Unquantized Resolution Conversion of Bitmap Images Using Error Diffusion", by Coward et al., now U.S. Pat. No. 5,363,213, Filed Jun. 8, 1992. Additionally, the following U.S. Patents relate to the area of resolution conversion: U.S. Pat. Nos. 4,742,553; 5,025,325; 4,829,587; 4,783,838; 5,226,094; 5,208,871; 5,185,674; 4,068,266; 4,827,352; 5,221,976; 4,975,785; 4,569,081; 4,528,693; 5,113,455.
All references cited in this specification, and their references, are incorporated by reference herein where appropriate for appropriate teachings of additional or alternative details, features, and/or technical background.